Re: [Scikit-learn-general] SVM for feature selection

: Eraldo Pomponi [eraldo.pomp...@gmail.com] Sent: Tuesday, April 28, 2015 5:14 PM To: scikit-learn-general@lists.sourceforge.net Subject: Re: [Scikit-learn-general] SVM for feature selection Dear Roberto, Just in case you want to better understand what Sebastian suggested, let me suggest you two

Re: [Scikit-learn-general] SVM for feature selection

y, April 28, 2015 4:53 PM > To: scikit-learn-general@lists.sourceforge.net > Subject: Re: [Scikit-learn-general] SVM for feature selection > > Yes, PCA would work too, but then you'll get feature extraction instead of > feature selection :) > > >> On Apr 28, 2015,

Re: [Scikit-learn-general] SVM for feature selection

No, because each component will use all features (PCA coefficients are dense) On 04/28/2015 05:05 PM, Pagliari, Roberto wrote: hi Sebastian, correct. however, if you set the number of components, you should get feature selection as well. Thank you, -

Re: [Scikit-learn-general] SVM for feature selection

> *From:* Sebastian Raschka [se.rasc...@gmail.com] > *Sent:* Tuesday, April 28, 2015 3:20 PM > *To:* scikit-learn-general@lists.sourceforge.net > *Subject:* Re: [Scikit-learn-general] SVM for feature selection > > With the L1 regularization, you can't "control

Re: [Scikit-learn-general] SVM for feature selection

: Re: [Scikit-learn-general] SVM for feature selection Yes, PCA would work too, but then you'll get feature extraction instead of feature selection :) On Apr 28, 2015, at 4:45 PM, Pagliari, Roberto mailto:rpagli...@appcomsci.com>> wrote: Hi Sebastian, thanks for the hint. I think ano

Re: [Scikit-learn-general] SVM for feature selection

arn-general@lists.sourceforge.net> > Subject: Re: [Scikit-learn-general] SVM for feature selection > > With the L1 regularization, you can't "control" the exact number of features > that will be selected, it depends on the data (which features are > irrelevant), and

Re: [Scikit-learn-general] SVM for feature selection

To: scikit-learn-general@lists.sourceforge.net Subject: Re: [Scikit-learn-general] SVM for feature selection With the L1 regularization, you can't "control" the exact number of features that will be selected, it depends on the data (which features are irrelevant), and the regular

Re: [Scikit-learn-general] SVM for feature selection

With the L1 regularization, you can't "control" the exact number of features that will be selected, it depends on the data (which features are irrelevant), and the regularization strength. What it basically does is zero-ing out coefficients. If you want to experiment with the number of features

[Scikit-learn-general] SVM for feature selection

>From the documentation: "Feature selection is usually used as a pre-processing step before doing the actual learning. The recommended way to do this in scikit-learn is to use a sklearn.pipeline.Pipeline